Integration of data mining classification techniques and ensemble learning to identify risk factors and diagnose ovarian cancer recurrence

Highlights：

• This study applied advanced machine learning techniques, widely considered as the most successful method to produce objective to predict the recurrent ovarian cancer.

• To study the benefit of adjuvant therapy, clinical trials should randomize patients stratified by these prognostic factors, to improve surveillance after treatment might lead to earlier detection of relapse, and provide decision makers the effective support for quality clinical decision making.

• In addition, the content of this study was highly related to the top of special issue “Machine Learning and Graph Analytics in Computational Biomedicine”.